Papua New Guinea - Women's share of population ages 15+ living with HIV (%)

Women's share of population ages 15+ living with HIV (%) in Papua New Guinea was 59.50 as of 2020. Its highest value over the past 30 years was 59.50 in 2020, while its lowest value was 39.80 in 1990.

Definition: Prevalence of HIV is the percentage of people who are infected with HIV. Female rate is as a percentage of the total population ages 15+ who are living with HIV.

Source: UNAIDS estimates.

See also:

Year Value
1990 39.80
1991 42.40
1992 44.20
1993 46.20
1994 47.90
1995 49.40
1996 50.70
1997 51.90
1998 52.80
1999 53.60
2000 54.30
2001 54.80
2002 55.20
2003 55.50
2004 55.80
2005 56.00
2006 56.20
2007 56.30
2008 56.40
2009 56.50
2010 56.50
2011 56.70
2012 57.00
2013 57.30
2014 57.60
2015 57.90
2016 58.20
2017 58.50
2018 58.80
2019 59.20
2020 59.50

Limitations and Exceptions: The limited availability of data on health status is a major constraint in assessing the health situation in developing countries. Surveillance data are lacking for many major public health concerns. Estimates of prevalence and incidence are available for some diseases but are often unreliable and incomplete. National health authorities differ widely in capacity and willingness to collect or report information.

Statistical Concept and Methodology: HIV prevalence rates reflect the rate of HIV infection in each country's population. Low national prevalence rates can be misleading, however. They often disguise epidemics that are initially concentrated in certain localities or population groups and threaten to spill over into the wider population. In many developing countries most new infections occur in young adults, with young women especially vulnerable. Data on HIV are from the Joint United Nations Programme on HIV/AIDS (UNAIDS). Changes in procedures and assumptions for estimating the data and better coordination with countries have resulted in improved estimates of HIV and AIDS. The models, which are routinely updated, track the course of HIV epidemics and their impact, making full use of information in HIV prevalence trends from surveillance data as well as survey data. The models take into account reduced infectivity among people receiving antiretroviral therapy (which is having a larger impact on HIV prevalence and allowing HIV-positive people to live longer) and allow for changes in urbanization over time in generalized epidemics. The estimates include plausibility bounds, which reflect the certainty associated with each of the estimates.

Aggregation method: Weighted average

Periodicity: Annual

Classification

Topic: Health Indicators

Sub-Topic: Risk factors